Analysis of U.S. industries based on Fama-French five-factor model under COVID-19

Abstract

At the end of 2019, COVID-19 swept the world, and the United States was also hit hard. The epidemic is not only a public health crisis, but also an economic crisis. Human beings’ lifestyles have undergone tremendous changes, such as reducing dine-in meals and suspending travel plans. Meanwhile, service industry that relies on interactions between customers and suppliers has been hit hard due to controlling of social distancing. This paper intends to explore the effectiveness of the Fama-French five-factor model in various industries in the United States under COVID-19 and find the changes the epidemic has brought. This paper will perform multiple regression analysis on the daily data of the five factors and industry stock portfolios obtained from the Kenneth R French database to obtain relevant results, and further analyze the model. The results show that the fitting degree of the model to the industries has improved after the epidemic. The HML factor of the service industry and the CMA factor of the paper industry have changed from significant to insignificant, while the RMW factor of the meal industry has changed from an insignificant factor to a significant one. These results reflect changes in the explanatory power of different factors for different industries under the epidemic, which reflect the severe impacts of COVID-19 on various industries in the United States, and provide new insights to better understand the Fama-French five-factor model.